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UV photography of the earth and the moon

The fundamental aim of this experiment was the acquisition of ultraviolet photographs of the earth and the moon that could be used to interpret similar imagery of Mars and Venus. Venus shows no markings whatever when viewed in visible light, a phenomenon that is in keeping with its immensely thick atmosphere and perpetual cloud cover, but in the near ultraviolet, the planet exhibits low contrast markings which vary in position and appearance with time. Mars posed just the opposite problem from Venus at wavelengths below 4500 A, Mars shows very little detail, sometimes none at all, whereas at longer wavelengths, the surface is clearly visible. Occasionally observers have reported that this obscuration has lifted and the ground has become visible at the shorter wavelengths as well. Such events have been labeled blue clearings and led to the suggestion that the ultraviolet obscuration was caused by an atmospheric haze. Mariner 6 and 7 observations of Mars failed to find such a haze and lent support to the alternative view that ascribed the absence of detail on UV photographs to a simple lack of contrast between Martian surface features at these wavelengths.

Source record↗

A computational method to model radar return range in a polygonally based, computer-generated-imagery simulation

Described is a method for modeling a ground-mapping radar system for use in simulations where the terrain is in a polygonal form commonly used with computer generated imagery (CGI). The method employs a unique approach for rapidly rejecting polygons not visible to the radar to facilitate the real-time simulation of the radar return. This rapid rejection of the nonvisible polygons requires the precalculation and storage of a set of parameters that do not vary during the simulation. The calculation of a radar range as a function of the radar forward-looking angle to the CGI terrain is carried out only for the visible polygons. This method was used as part of a simulation for terrain-following helicopter operations on the vertical motion simulator at the NASA Ames Research Center. It proved to be an efficient means for returning real-time simulated radar range data.

Moran, F. J.↗

A View from Above: Earth Observations

Since the 1960s, satellites have been looking down at the Earth to monitor weather patterns and track severe storms, observe how our land surface is changing and responding to hydrometerological extremes, and even to sense how the Earth's crust is deforming from earthquakes and volcanoes. Space and airborne platforms can provide unique views of the disaster lifecycle, informing pre-event mitigation and preparedness, emergency response following an event, and monitoring longer-term recovery. These remotely-sensed data, products and models can provide a global perspective to see beyond administrative boundaries, reach remote places where in situ observations are di cult or non-existent, and provide the necessary context and situational awareness to aid in disaster response. So how do these platforms work? Instruments aboard satellites use different portions of the electromagnetic spectrum to passively or actively observe energy across a range of wavelengths, which can be turned into meaningful data on geophysical, atmospheric, and hydrological variables. e US has had a broad range of Earth observation (EO) platforms delivering open data for scientific research and societal benefits for decades. e Landsat programme, a joint initiative between the US Geological Survey (USGS) and NASA, has the world's longest continuous collection of space-based satellite imagery of the Earth, extending from 1972 to present. e Landsat satellites provide visible, near infrared, and thermal data that are used to support emergency response and disaster relief by mapping changes in water during floods, and dramatic land surface changes, including those resulting from landslides, wild res, severe weather, volcanic plumes, and dust storms.

FEMA↗

Generalized Geologic evaluation of side looking radar imagery of the Teton Range and Jackson Hole, northwestern Wyoming

A generalized geologic evaluation of lines, localities, and features of various types that are visible on a series of radar image strips covering the Teton Range and Jackson Hole in northwestern Wyoming, is given. No attempt was made to collate a complete geologic map with the radar image at each locality. Formation names, problems of geologic interpretation, and details of stratigraphy and structure that are not directly pertinent to a study of the imagery are omitted, but reference is made to publications that contain this type of supplementary information.

Love, J. D.↗

Symbology Development for General Aviation Synthetic Vision Primary Flight Displays for the Approach and Missed-Approach Modes of Flight

Spatial disorientation induced by inadvertent flight into instrument meteorological conditions (IMC) continues to be a leading cause of fatal accidents in general aviation. The Synthetic Vision Systems General Aviation (SVS-GA) research element, an integral part of NASA s Aviation Safety and Security Program (AvSSP), is investigating a revolutionary display technology designed to mitigate low visibility events such as controlled flight into terrain (CFIT) and low-visibility loss of control (LVLoC). The integrated SVS Primary Flight Display (SVS-PFD) utilizes computer generated 3-dimensional imagery of the surrounding terrain augmented with flight path guidance symbology. This unique combination will provide GA pilots with an accurate representation of their environment and projection of their flight path, regardless of time of day or out-the-window (OTW) visibility. The initial Symbology Development for Head-Down Displays (SD-HDD) simulation experiment examined 16 display configurations on a centrally located high-resolution PFD installed in NASA s General Aviation Work Station (GAWS) flight simulator. The results of the experiment indicate that situation awareness (SA) can be enhanced without having a negative impact on flight technical error (FTE), by providing a general aviation pilot with an integrated SVS display to use when OTW visibility is obscured.

Bartolone, Anthony P.↗

Study to develop improved spacecraft snow survey methods using Skylab/EREP data

The author has identified the following significant results. The initial analysis of EREP data from the SL-2 mission has been undertaken. Snow distributions are being mapped from the S190A photography for three mountain areas: the Sierra Nevadas; the Cascades near Washington-Oregon border; and the Wasatch Range in Utah. In the S192 screening film, a dramatic reversal in the reflectance of the snow in the Wasatch Range is observed between the visible and near IR channels. In channel 2 (0.46 - 0.51 microns) the snow has a high reflectance, whereas in channel 11 (1.55 - 1.75 microns) the snow appears almost black, having a much lower reflectance than the surrounding terrain. The sharp drop in reflectance in the near IR channel is believed to be due to the existence of melt water on the snow surface. Although investigators have reported this effect previously using ERTS-1 imagery, the S192 data provides the first opportunity to study quantitatively the snow reflectance in several visible and near IR channels. The results will have direct application for developing a technique to determine the condition of the snow surface (i.e., dry of melting), a significant parameter in snow hydrology.

Barnes, J. C.↗

Onboard Algorithms for Data Prioritization and Summarization of Aerial Imagery

Many current and future NASA missions are capable of collecting enormous amounts of data, of which only a small portion can be transmitted to Earth. Communications are limited due to distance, visibility constraints, and competing mission downlinks. Long missions and high-resolution, multispectral imaging devices easily produce data exceeding the available bandwidth. To address this situation computationally efficient algorithms were developed for analyzing science imagery onboard the spacecraft. These algorithms autonomously cluster the data into classes of similar imagery, enabling selective downlink of representatives of each class, and a map classifying the terrain imaged rather than the full dataset, reducing the volume of the downlinked data. A range of approaches was examined, including k-means clustering using image features based on color, texture, temporal, and spatial arrangement

Chien, Steve A.↗

Snow survey from space, with emphasis on the results of the analysis of Skylab EREP S192 multispectral scanner data

The Skylab EREP S192 multispectral scanner data have provided an opportunity to examine the reflectance characteristics of snow cover in several spectral bands extending from the visible into the near infrared spectral region to about 2 microns. The analysis of the S192 imagery and digital tape data from five EREP passes, two from the SL-2 mission and three from the SL-4 mission, indicates a sharp drop in reflectance of snow in the near infrared, with snow becoming essentially nonreflective in Bands 11 (1.55-1.75 microns) and 12 (2.10-2.35 microns). The results are in good agreement with the results of laboratory experiments. Two potential applications to snow mapping of measurements in the near infrared spectral region are possible: (1) the use of a near infrared band in conjunction with a visible band to distinguish automatically between snow and water droplet clouds, and (2) the use of one or more near infrared bands to detect areas of melting snow.

Barnes, J. C.↗

An Expert System for Autonomous Spacecraft Control

The Autonomous Sciencecraft Experiment (ASE), part of the New Millennium Space Technology 6 Project, is flying onboard the Earth Orbiter 1 (EO-1) mission. The ASE software enables EO-1 to autonomously detect and respond to science events such as: volcanic activity, flooding, and water freeze/thaw. ASE uses classification algorithms to analyze imagery onboard to detect chang-e and science events. Detection of these events is then used to trigger follow-up imagery. Onboard mission planning software then develops a response plan that accounts for target visibility and operations constraints. This plan is then executed using a task execution system that can deal with run-time anomalies. In this paper we describe the autonomy flight software and how it enables a new paradigm of autonomous science and mission operations. We will also describe the current experiment status and future plans.

utonomy flight software↗

Short-Term Prediction Research and Transition (SPoRT) Center: Transitioning Satellite Data to Operations

The Short-term Prediction Research and Transition (SPoRT) Center located at NASA Marshall Space Flight Center has been conducting testbed activities aimed at transitioning satellite products to National Weather Service operational end users for the last 10 years. SPoRT is a NASA/NOAA funded project that has set the bar for transition of products to operational end users through a paradigm of understanding forecast challenges and forecaster needs, displaying products in end users decision support systems, actively assessing the operational impact of these products, and improving products based on forecaster feedback. Aiming for quality partnerships rather than a large quantity of data users, SPoRT has become a community leader in training operational forecasters on the use of up-and-coming satellite data through the use of legacy instruments and proxy data. Traditionally, SPoRT has supplied satellite imagery and products from NASA instruments such as the Moderate-resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS). However, recently, SPoRT has been funded by the GOES-R and Joint Polar Satellite System (JPSS) Proving Grounds to accelerate the transition of selected imagery and products to help improve forecaster awareness of upcoming operational data from the Visible Infrared Imager Radiometer Suite (VIIRS), Cross-track Infrared Sounder (CrIS), Advanced Baseline Imager (ABI), and Geostationary Lightning Mapper (GLM). This presentation provides background on the SPoRT Center, the SPoRT paradigm, and some example products that SPoRT is excited to work with forecasters to evaluate.

Zavodsky, Bradley↗

A data base of ASAS digital imagery

The Advanced Solid-State Array Spectroradiometer (ASAS) is an airborne, off-nadir tilting, imaging spectroradiometer that acquires digital image data for 29 spectral bands in the visible and near-infrared. The sensor is used principally for studies of the bidirectional distribution of solar radiation scattered by terrestial surfaces. ASAS has acquired data for a number of terrestial ecosystem field experiments and investigators have received over 170 radiometrically corrected, multiangle, digital image data sets. A database of ASAS digital imagery has been established in the Pilot Land Data System (PLDS) at the NASA/Goddard Space Flight Center to provide access to these data by the scientific community. ASAS, its processed data, and the PLDS are described, together with recent improvements to the sensor system.

Irons, James R.↗

Techniques for diagnosing mesoscale phenomena affecting aviation using VAS satellite data

A major advance in geostationary satellite observations occurred recently with the inclusion of an experimental instrument aboard the latest Geostationary Operational Environmental Satellites (GOES). This instrument, called the Visible Infrared Spin-Scan Radiometer (VISSR) Atmospheric Sounder (VAS), permits simultaneous observations of the atmosphere in up to 12 infrared channels, in addition to the visible image. In the present investigation, particular emphasis is placed on the ability of VAS imagery and derived soundings to delineate isolated, meso-scale regions of convective instability. The results of the investigation point to the ability of the VAS instrument to delineate meteorologically meaningful patterns of low-level moisture and mid-level dryness and to the utility of the image overlay procedure for isolating, in real time, regions of convective potential, at time and space scales unresolvable using radiosonde data alone.

Petersen, R. A.↗

Star formation in NGC 4449: MAMA-detector UV imagery and Fabry-Perot Balmer-line imagery

Using far-ultraviolet (FUV) and Balmer-line imagery, we investigate the star formation history of 22 large OB complexes in the Magellanic irregular galaxy NGC 4449. The FUV luminosity of NGC 4449 is comparable to those of late-type spirals and is greater than that of the LMC by approximately 2.4 mag, indicating substantial star formation in the last 10(exp 8) yr. FUV data were taken using a sounding-rocket telescope with a Multianode Microchannel Array (MAMA) detector, and Balmer-line data were taken using the Goddard Fabry-Perot Imager. The resulting imagery shows bright, roughly coincident FUV and H alpha sources throughout the extent of the visible galaxy. We model these sources using cluster-evolution codes. Although all sources are a few Myr old, clear age differences are found. In particular, several of the most recently active star formation regions are located together in the galaxy's northern periphery, which is apparently coincident with a large H I reservoir. The brightest and most massive OB complexes are found along the northeast-southwest surface brightness ridgeline (the 'bar'). Over the entire galaxy, star formation rates are consistent on timescales of 10(exp 6), 10(exp 8), and 10(exp 9) yr. A history of recent star formation is suggested with two main episodes, one predominantly in the bar ending approximately 5 Myr ago, and an ongoing one associated with an observed H I cloud.

Hill, Robert S.↗

Synthetic Vision Systems

A synthetic vision system is an aircraft cockpit display technology that presents the visual environment external to the aircraft using computer-generated imagery in a manner analogous to how it would appear to the pilot if forward visibility were not restricted. The purpose of this chapter is to review the state of synthetic vision systems, and discuss selected human factors issues that should be considered when designing such displays.

Prinzel, L.J.↗

Creating IR-verified Gridded Fire Burn Maps using Public NASA and Satellite Data

Even though fire can be devastating, wildland fire is a natural and integral force on our landscapes, providing value by decreasing fuels at the Wildland Urban Interface (WUI) to promote safe communities. However, uncontained wildfires can devastate communities, threaten our health, and result in substantial economic losses. There has been greater than a $50B increase in wildfire insurance claims from 2017-2021, which has been exacerbated by climate change. Our partners at Kettle reinsurance are focused on building a smarter reinsurance model for protecting today’s globalized world from the catastrophic effects of climate change. Our objective is to develop a high-confidence grid-based wildfire burn product using multiple sources of satellite data to determine whether a ‘conflagration' (fire larger than 999+ acres) has ‘breached’ a grid cell. This product will substantially decrease the time it takes for homeowners to receive payouts, from over a year to a couple months. Working with our partners at Kettle reinsurance, we use VIIRS (Visible Infrared Imaging Radiometer Suite) 375 m fire detections and Sentinel-2 10 m satellite imagery to create a 20-m gridded fire burn product. Our process is based on the level of confidence in the data source and takes into account vegetation change throughout the life of the fire. For example, Sentinel-2 vegetation-change indices have a higher level of confidence when congruent with VIIRS active-fire detection data, rather than VIIRS detections alone. We have also verified our fire burn product against MODIS/ASTER Airborne Simulator (MASTER) Infrared (IR) data from the Fire Influence on Regional to Global Environments Experiment - Air Quality (FIREX-AQ) 2019 campaign, with 88% overall agreement. The first iteration has been developed for responding to wildfires in California, with the possibility to expand nationwide and globally.

Emily Gargulinski↗

Pattern recognition analysis of polar clouds during summer and winter

A pattern recognition algorithm is demonstrated which classifies eighteen surface and cloud types in high-latitude AVHRR imagery based on several spectral and textural features, then estimates the cloud properties (fractional coverage, albedo, and brightness temperature) using a hybrid histogram and spatial coherence technique. The summertime version of the algorithm uses both visible and infrared data (AVHRR channels 1-4), while the wintertime version uses only infrared data (AVHRR channels 3-5). Three days of low-resolution AVHRR imagery from the Arctic and Antarctic during January and July 1984 were analyzed for cloud type and fractional coverage. The analysis showed significant amounts of high cloudiness in the Arctic during one day in winter. The Antarctic summer scene was characterized by heavy cloud cover in the southern ocean and relatively clear conditions in the continental interior. A large region of extremely low brightness temperatures in East Antarctica during winter suggests the presence of polar stratospheric cloud.

Ebert, Elizabeth E.↗

International Space Station Data Collection for Disaster Response

Natural disasters - including such events as tropical storms, earthquakes, floods, volcanic eruptions, and wildfires -effect hundreds of millions of people worldwide, and also cause billions of dollars (USD) in damage to the global economy. Remotely sensed data acquired by orbital sensor systems has emerged as a vital tool to identify the extent of damage resulting from a natural disaster, as well as providing near-real time mapping support to response efforts on the ground and humanitarian aid efforts. The International Space Station (ISS) is a unique terrestrial remote sensing platform for acquiring disaster response imagery. Unlike automated remote-sensing platforms it has a human crew; is equipped with both internal and externally-mounted remote sensing instruments; and has an inclined, low-Earth orbit that provides variable views and lighting (day and night) over 95 percent of the inhabited surface of the Earth. As such, it provides a useful complement to free-flyer based, sun-synchronous sensor systems in higher altitude polar orbits. While several nations have well-developed terrestrial remote sensing programs and assets for data collection, many developing nations do not have ready access to such resources. The International Charter, Space and Major Disasters (also known as the "International Disaster Charter", or IDC; http://www.disasterscharter.org/home) addresses this disparity. It is an agreement between agencies of several countries to provide - on a best-effort basis - remotely sensed data of natural disasters to requesting countries in support of disaster response. The lead US agency for interaction with the IDC is the United States Geological Survey (USGS); when an IDC request or "activation" is received, the USGS notifies the science teams for NASA instruments with targeting information for data collection. In the case of the ISS, the Earth Sciences and Remote Sensing (ESRS) Unit, part of the Astromaterials Research and Exploration Science Directorate and supporting the ISS Program Science Office at NASA's Johnson Space Center, receives notification from the USGS and coordinates targeting and data collection with the NASA ISS sensor teams. If data is collected, it is passed back to the USGS for posting on their Hazards Data Distribution System and made available for download. The ISS International Partners (CSA, ESA, JAXA, Roscosmos/Energia) have their own procedures for independently supporting IDC activations using their assets on ISS, and there is currently no joint coordination with NASA ISS sensor teams. Following completion of ISS assembly, NASA remote sensing assets began collecting IDC response data in May 2012. The initial NASA ISS sensor systems available to respond to IDC activations included the ISS Agricultural Camera (ISSAC), an internal multispectral visible-near infrared wavelength system mounted in the Window Observational Research Facility, or WORF; the Crew Earth Observations (CEO) Facility, where the crew collects imagery through Station windows using off-the-shelf handheld digital visible-wavelength cameras; and the Hyperspectral Imager for the Coastal Oceans (HICO), a visible to near-infrared system mounted externally on the Japan Experiment Module Exposed Facility. The ISSAC completed its primary mission and was removed from the WORF in January 2013. It was replaced by the very high resolution ISS SERVIR Environmental Research and Visualization System (ISERV) Pathfinder, a visible-wavelength digital camera, telescope, and pointing system. Since the start of IDC response by NASA sensors on the ISS in May 2012 and as of this report, there have been eighty IDC activations; NASA sensor systems have collected data for twenty-three of these events. Of the twenty-three successful data collections, five involved 2 or more ISS sensor systems responding to the same event. Data has also been collected by International Partners in response to natural disasters, most notably JAXA and Roscosmos/Energia through the Urugan program. Data collected in response to IDC activations is delivered by the ISS sensor teams to the ESRS for quality review and transfer to the USGS, where it is ingested into the Hazards Data Distribution System, or HDDS (https://hdds.usgs.gov/hdds2/; figure 1). This system allows the local agencies that issued the IDC activation request to review and download data. The data is then used to develop secondary products useful for humanitarian response such as flood maps. As of this report, approximately 1000 images collected by NASA ISS sensor systems have been downloaded from the HDDS, indicating that the ISS has assumed a valuable role in disaster response efforts. The ISS is also a unique platform in that it will have multiple users over its lifetime, and that no single remote sensing system has a permanent internal or external berth. This scheduled turnover provides for development of new remote sensing capabilities relevant to disaster response -as well as both research and applied science-and represents a significant contribution to continuance and enhancement of the NASA mission to investigate changes on our home planet.

Stefanov, William L.↗